OpenAI unveils custom chip to boost AI performance and efficiency

OpenAI announced the first measured performance results from Jalapeño, its first custom inference chip. On InferenceX, a public benchmark using GPT‑OSS 120B, Jalapeño delivered more peak throughput per kilowatt and lower token latency than commercial systems in the comparison. It also performed strongly on DeepSeek R1 and Kimi K2, showing its gains extend across model families. The chip gives OpenAI greater control over how its models run and the economics of serving them. By developing the model, serving software, chip, memory, and network together, the company can improve throughput, latency, energy efficiency, and cost as one system. It creates a credible first-party path alongside accelerators from other partners, expanding the ability to match each workload to the strongest system at the right economics. Future generations of the chip are already underway. Different workloads place different demands on the system. Frontier training, high-volume inference, and always-on agents have different requirements across chips, software, networks, power, and latency. OpenAI’s goal is to stay on the Pareto frontier, continually seeking the strongest mix of capability, speed, reliability, efficiency, and cost for each workload. Different chips and providers lead on different dimensions, and the frontier keeps moving. OpenAI’s portfolio includes Microsoft’s compute, NVIDIA’s chips, AWS, AMD, Broadcom, Cerebras, CoreWeave, Oracle, SB Energy, and SoftBank. Each brings different strengths across cloud infrastructure, accelerated computing, low-latency inference, data-center development, and energy delivery. The company actively manages this portfolio for both capability and economics, using premium systems where capability matters most and optimizing for efficiency where scale and cost matter more. Preserving credible choice across providers, hardware, and deployment models lets OpenAI direct demand toward the strongest performance per dollar, maintain pricing discipline as market conditions change, and move with the frontier as stronger technology emerges. Direct control adds leverage where tighter integration can improve the entire system. The company partners where the ecosystem helps it move faster and builds where co-design creates a meaningful advantage. Data centers also create a point of leverage. Project Camellia in Georgia shows how OpenAI can design facilities around customer workloads while creating jobs, supporting local businesses, covering project infrastructure and energy costs, conserving water through a closed-loop system, and subjecting its commitments to an annual independent public audit. The value of this system is measured by what it produces: more useful intelligence from every unit of compute. Better models reach the right answer with fewer attempts. Smarter routing and context management reduce wasted work. Optimized software and purpose-built hardware improve speed and energy efficiency. On the Artificial Analysis Coding Agent Index, GPT‑5.6 Sol with max reasoning reached a new high while using 54% fewer output tokens than another leading model. For customers, improvements like these mean faster results, more dependable products, fewer retries, agents that complete longer workflows, and a lower total cost for successful work. The best economics come from useful intelligence per dollar. As useful intelligence becomes more capable and affordable, more work becomes economically practical. A company can provide tailored analysis to every customer, review every contract, run live financial scenarios, and help engineers test more ideas. This is Jevons paradox: greater efficiency makes more uses worthwhile, expanding consumption and creating new economic activity through more work completed, better decisions, more products launched, and more revenue generated. More productive compute and a more competitive supply base help OpenAI serve more customers at lower cost and carry those efficiency gains through to users. Growth funds continued investment in research, infrastructure, and safety. That is OpenAI’s compounding advantage: better technology creates better economics, better economics fund the next wave of progress, and every gain makes the whole system stronger.